In the medical field, the digitization of the medical images obtained by imaging objects has been implemented. This makes it possible to monitor-display the medical image data output from medical imaging apparatuses such as a CR apparatus, a CT apparatus, an MRI apparatus, and an ultrasonic apparatus at the time of diagnosis. A doctor then makes diagnosis by interpreting such monitor-displayed medical images and observing the state of a morbid region and its temporal change. Note that CR, CT, and MRI respectively stand for Computed Radiography, Computed Tomography, and Magnetic Resonance Imaging.
Conventionally, a medical image processing apparatus called a computer-aided diagnosis apparatus which can automatically detect a morbid region as an abnormal shadow candidate by image analysis on medical image data has been developed to reduce the load on a doctor making diagnosis.
This medical image processing apparatus can detect abnormal shadow candidates such as an abnormal tumor shadow indicating a cancer or the like and a high-density micro calcification shadow based on input medical image data. Automating part of diagnosing operation by the doctor in this manner can reduce the load on the doctor making diagnosis and improve the accuracy of a diagnosis result.
In making diagnosis based on medical images, the doctor needs to create a report concerning an interpretation result as a diagnosis result in addition to interpreting a medical image. The operation of creating this report also imposes a very heavy load on the doctor.
On the other hand, a medical image processing apparatus which allows to create a report concerning an interpretation result by only selecting a form text which is created in advance when interpretation results are input has been proposed to reduce the load of the operation of creating such reports (see, for example, Japanese Patent Laid-Open No. 2004-167087).
In the case of Japanese Patent Laid-Open No. 2004-167087, however, since a report is created by filling in blanks concerning the respective items with selected character strings in the mode defined by a form text, expressions about an interpretation result are limited.
It is also effective to use a so-called input prediction technique of displaying words/sentences, as conversion candidates, concerning a character which is being input instead of a form text. The conventional input prediction technique is designed to display words with high input frequencies and recently input words at higher ranks in conversion candidates. That is, this technique is not designed to preferentially display words/sentences suitable for interpreted medical images. Even if, therefore, the input prediction technique is used, it is not necessarily possible to efficiently create a report.